Investment Rating - The report assigns a "Buy" rating for the company with a target price of $133.02 based on a 20X PE for 2026 [4]. Core Views - The company is a leading manufacturer of ASIC servers and Ethernet switches, benefiting from the growth in AI inference demand, particularly from major cloud service providers in North America [2][3]. - The company is expected to recover from a short-term decline in server revenue due to Google's TPU product transition, with anticipated growth resuming in the second half of 2025 [2]. - The company is actively expanding its customer base for ASIC servers, having become a supplier for Meta and secured a project with a leading commercial AI company [2][3]. Summary by Sections 1. Deep Layout in ASIC Servers and Ethernet Switches - The importance of inference computing power is increasing, and the ASIC industry chain is expected to benefit from this trend [14]. - The company is positioned to benefit from the volume growth of ASIC servers and the expansion of its customer base, particularly with Google and Meta [27][31]. - The Ethernet switch business is poised to grow due to the trend of AI Ethernet networking, with increased demand for high-speed switches [32]. 2. Transition from EMS to ODM - The company is shifting from an EMS model to an ODM model, which is expected to enhance customer binding and improve profitability [47]. - The revenue from the hardware platform solutions (ODM) is projected to grow significantly, contributing to overall revenue growth [50][52]. - The company's gross margin and operating profit margin have been steadily increasing due to the growth of its ODM business [52]. 3. ASIC Industry and Company Alpha - The company is well-positioned in the ASIC server and Ethernet ODM switch market, benefiting from industry trends and new customer acquisitions [3][4]. - The company’s net profit is forecasted to grow significantly over the next few years, with expected profits of $593 million, $765 million, and $871 million for 2025, 2026, and 2027 respectively [4][8]. - The company is expected to gain market share as it expands its customer base and increases the complexity of its products [31]. 4. Profit Forecast and Investment Recommendations - The company’s revenue is projected to grow from $7.96 billion in 2023 to $15.89 billion in 2027, with a compound annual growth rate (CAGR) of approximately 14.1% [8]. - The EBITDA is expected to increase from $467 million in 2023 to $1.296 billion in 2027, reflecting strong operational performance [8].

Core Viewpoint - Nvidia holds a dominant position in the AI semiconductor field, with an estimated market share exceeding 80% in data center chips and products like ChatGPT and Claude [1] Group 1: Nvidia's Market Position - Nvidia's leadership in AI computing can be traced back nearly two decades, with the development of its CUDA software stack [1] - Despite being in a loss-making position for much of its early years, Nvidia's CEO Jensen Huang recognized the potential of GPUs for AI [1] - Nvidia's products now dominate a significant portion of global AI applications [1] Group 2: Competitors - AMD is Nvidia's largest competitor in the data center AI computing market, launching its MI300 GPU in 2024, over a year later than Nvidia's second-generation data center GPU [3] - Analysts predict AMD's market share to be less than 15%, but the company is focused on improving its software capabilities [3] - Custom-designed chips (ASICs) are emerging as a challenge to Nvidia, with a projected market size doubling by 2025 [4] - Major companies like Amazon and Google are designing their own chips, such as Amazon's Trainium and Google's TPU, to provide cheaper alternatives for AI workloads [6] Group 3: Emerging Threats - Huawei is considered a significant competitor to Nvidia, with reports indicating that its AI chip innovations are catching up [9] - Numerous startups are also challenging Nvidia with new chip designs and business models, including companies like Cerebras and Groq [11]

Investment Rating - The report assigns a positive outlook for MediaTek, indicating a potential for growth in the upcoming quarters, particularly in the AI and mobile sectors [2][3]. Core Insights - MediaTek's Q1 2025 revenue reached NT$153.3 billion, showing a quarter-over-quarter increase of 11.1% and a year-over-year increase of 14.9%. Operating profit was NT$30.1 billion, with a net profit of NT$29.5 billion [2][7]. - The demand recovery in mainstream and entry-level markets has driven growth in the mobile business, with expectations for further market share and average selling price (ASP) increases with the upcoming flagship SoC launch [2][14]. - MediaTek is collaborating with NVIDIA to target the AI ASIC market, projecting AI ASIC revenue to reach $1 billion by 2026 [3][28]. Summary by Sections Overall Performance - In Q1 2025, MediaTek achieved a revenue of NT$153.3 billion, with operating profit at NT$30.1 billion and net profit at NT$29.5 billion. The gross margin was 48.1%, reflecting a slight decline from the previous quarter and year [7][14]. Business Segmentation - **Mobile Business**: Contributed 56% to total revenue, with a 6% increase year-over-year and quarter-over-quarter, driven by demand recovery in mainstream and entry-level markets [14]. - **Intelligent Edge Platform**: Accounted for 39% of total revenue, showing a 32% year-over-year and 23% quarter-over-quarter increase, benefiting from upgrades in connectivity technology and AI applications [15]. - **Power IC Business**: Made up 5% of total revenue, with a 7% year-over-year increase but a 9% quarter-over-quarter decline [16]. Performance Guidance - For Q2 2025, MediaTek expects revenue to be between NT$147.2 billion and NT$159.4 billion, with a projected gross margin of 47% (±1.5 percentage points) [17][18].

Core Viewpoint - Apple's decision to purchase approximately $1 billion worth of NVIDIA's GB300 NVL72 GPU cluster servers marks a significant shift in its AI strategy, acknowledging the advantages of the GPU ecosystem and generative AI paradigm over its self-developed chips [1][3][21]. Group 1: Apple's Shift to NVIDIA - Apple has historically relied on its self-developed chips, achieving great success with its Apple Silicon series in mobile and edge computing [3]. - The recent order for NVIDIA's GPUs indicates Apple's recognition of the GPU ecosystem's superiority in the generative AI space, driven by urgent market demands for high-performance computing [3][4]. - Analysts suggest that Apple plans to order around 250 NVL72 servers, with each server costing between $3.7 million and $4 million, totaling nearly $1 billion [3]. Group 2: Implications of Siri's Performance - Siri's declining competitiveness against rivals like Google Assistant and Alexa has prompted Apple to reassess its AI hardware strategy [4][5]. - The anticipated updates to Siri have been delayed, reflecting the challenges Apple faces in enhancing its AI capabilities [4][5]. Group 3: Generative AI and Market Dynamics - The rise of generative AI has redefined user expectations for intelligent assistants, shifting from simple command execution to intelligent collaboration [5]. - Apple's investment in NVIDIA GPUs is speculated to support the development of an Apple LLM, enhance Siri, and integrate AI into various applications [5][6]. Group 4: GPU vs. ASIC - The choice of NVIDIA's GPUs over self-developed ASICs highlights the critical importance of time and performance in the AI race, with NVIDIA's established ecosystem providing immediate solutions [8][16]. - NVIDIA's GPUs have become the de facto standard for training large language models (LLMs), showcasing their performance and ecosystem maturity [8][11]. - The high cost of NVIDIA GPUs, which have surged to $90,000 each, reflects their dominant market position, with NVIDIA reporting a revenue of $39.3 billion and a gross margin exceeding 70% [8][9]. Group 5: Future Outlook - Despite the current preference for NVIDIA GPUs, Apple may still pursue a hybrid strategy, utilizing NVIDIA for model training while relying on its own chips for inference [6][19]. - The ongoing competition between ASICs and GPUs suggests that while ASICs may face challenges now, they are not entirely out of the picture for future applications [19][21].